The concept of “CAD” in the medical context, i.e., using a computer to search for abnormalities in a medical image, is well known. The acronym “CAD” has been used interchangeably to refer to any of the following terms: computer-aided detection, computer-assisted detection, computer-aided diagnosis, and computer-assisted diagnosis.
Recently, CAD systems have been developed that can search for cancerous or precancerous nodules in the lung by examining a three-dimensional volume of data acquired using x-ray CT (computed tomography). There have also been discussions of CAD algorithms that look for “pulmonary embolisms” (PE's) in those same three-dimensional volumes of data. A pulmonary embolism (PE) occurs when a clump of material such as a piece of plaque or a blood clot travels through the blood stream and becomes lodged in a pulmonary artery. Importantly, PE detection relies on the presence of a contrast medium, such as an iodinated agent, in the blood stream of the patient at the time of CT scanning. The contrast agent causes blood within the arteries to appear very brightly in the 3D medical image, and this facilitates PE detection because the PE's then show up as dark protrusions or discontinuities in the bright blood stream.
Workflow-related problems can arise because CAD nodule detection does not require the presence of the contrast agent in the patient, whereas CAD PE detection does require the presence of the contrast agent in the patient. Specifically, if the PE detection algorithm is performed by the CAD system when there has not been any contrast agent injected, there may be misleading results. Even worse, since the information systems used in the clinical environment can sometimes be erroneous regarding whether the contrast agent was introduced, it is not always reliable to depend on “header” information that might be associated with the CT scan for this crucial piece of information.
Similar workflow-related problems can arise in other circumstances where contrast agents are used in one type of detection algorithm and not in another type of detection algorithm performed on the same image volume.